Description

Book Synopsis
A concise, easy-to-read guide, introducing beginners to the engineering background of modern communication systems, from mobile phones to data storage. Assuming only basic knowledge of high-school mathematics and including many practical examples and exercises to aid understanding, this is ideal for anyone who needs a quick introduction to the subject.

Trade Review
'The book is nicely written, and is recommended as a textbook for a one-semester introductory course on coding and information theory.' Pushpa N. Rathie, Zentralblatt MATH

Table of Contents
1. Introduction Chung-Hsuan Wang; 2. Error-detecting codes Chung-Hsuan Wang; 3. Repetition and hamming codes Francis Lu; 4. Data compression: efficient coding of a random message; 5. Entropy and Shannon's source coding theorem; 6. Mutual information and channel capacity Jwo-Yuh Wu; 7. Achieving the Shannon limit by turbo coding; 8. Other aspects of coding theory Francis Lu.

A Students Guide to Coding and Information Theory

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    A Hardback by Stefan M. Moser, Po-Ning Chen

    £68.00

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    Order before 4pm today for delivery by Thu 15 Oct 2026.

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      Book details

      Published 1/26/2012 12:00:00 AM
      ISBN-13 9781107015838
      978-1107015838
      ISBN-10 1107015839

      Description

      Book Synopsis
      A concise, easy-to-read guide, introducing beginners to the engineering background of modern communication systems, from mobile phones to data storage. Assuming only basic knowledge of high-school mathematics and including many practical examples and exercises to aid understanding, this is ideal for anyone who needs a quick introduction to the subject.

      Trade Review
      'The book is nicely written, and is recommended as a textbook for a one-semester introductory course on coding and information theory.' Pushpa N. Rathie, Zentralblatt MATH

      Table of Contents
      1. Introduction Chung-Hsuan Wang; 2. Error-detecting codes Chung-Hsuan Wang; 3. Repetition and hamming codes Francis Lu; 4. Data compression: efficient coding of a random message; 5. Entropy and Shannon's source coding theorem; 6. Mutual information and channel capacity Jwo-Yuh Wu; 7. Achieving the Shannon limit by turbo coding; 8. Other aspects of coding theory Francis Lu.

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